IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20020079.html
   My bibliography  Save this paper

Detecting Serial Dependence in Tail Events

Author

Listed:
  • Cees Diks

    (CeNDEF, University of Amsterdam)

Abstract

A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as remaining ARCH or GARCH type structure in standardized residuals of financial time series. The new test can be implemented easily by slight modification of the standard BDS test, and is also suitable for model identification. The BDS test and the modified version are compared numerically. To enable fair power comparisons, both tests are implemented as exact level Monte Carlo tests, enabling power calculations of the tests at identical actual sizes. The Monte Carlo implementation allows the use of test statistics which are considerably simpler than for the standard BDS test. For all nonlinear stochastic time series models examined the power of the new test is found to be uniformly larger over all practically reasonable values of the bandwidth parameter. The test is illustrated with an empirical application.

Suggested Citation

  • Cees Diks, 2002. "Detecting Serial Dependence in Tail Events," Tinbergen Institute Discussion Papers 02-079/1, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20020079
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/02079.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Nonparametric tests; Serial dependence; Correlation integral; Monte Carlo tests; Volatility clustering.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20020079. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.